code: def avg_pool(
      kernel_size,
      stride=1,
      dilation=1,
      conv_type=ConvType.HYPERCUBE,
      in_coords_key=None,
      D=-1,
  ):
      assert D > 0, "Dimension must be a positive integer"
      region_type, axis_types, kernel_size = convert_conv_type(
          conv_type, kernel_size, D
      )
      kernel_generator = ME.KernelGenerator(
          kernel_size,
          stride,
          dilation,
          region_type=region_type,
          axis_types=axis_types,
          dimension=D,
      )
  
      return ME.MinkowskiAvgPooling(
          kernel_size=kernel_size,
          stride=stride,
          dilation=dilation,
          kernel_generator=kernel_generator,
          dimension=D,
      )
  
file_path: torch-points3d/torch_points3d/modules/MinkowskiEngine/common.py
imports: import collections
  from enum import Enum
  import torch.nn
  import MinkowskiEngine
label_desc: Use image node_id 6 for calling a global function with example usage: avg_pool(kernel_size, stride, dilation, conv_type, in_coords_key, D) and returns: ME